Utilizing fast memory devices to optimize different functions

ABSTRACT

A computing device includes an interface configured to interface and communicate with a dispersed storage network (DSN), a memory that stores operational instructions, and a processing module operably coupled to the interface and memory such that the processing module, when operable within the computing device based on the operational instructions, is configured to perform various operations. A computing device receives a data access request for an encoded data slice (EDS) associated with a data object. The computing device compares a slice name of the data access request with slice names stored within RAM. When the data access request slice name compares unfavorably with those stored slice names, the computing device transmits an empty data access response that includes no EDS to the other computing device without needing to access a hard disk drive (HDD) that stores EDSs. Alternatively, the computing device transmits a data access response that includes the EDS.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. § 120 as a continuation of U.S. Utility application Ser. No.15/362,615, entitled “UTILIZING FAST MEMORY DEVICES TO OPTIMIZEDIFFERENT FUNCTIONS,” filed Nov. 28, 2016, which claims prioritypursuant to 35 U.S.C. § 119(e) to U.S. Provisional Application No.62/260,735, entitled “ACCESSING COPIES OF DATA STORED IN A DISPERSEDSTORAGE NETWORK” filed Nov. 30, 2015, both of which are herebyincorporated herein by reference in their entirety and made part of thepresent U.S. Utility Patent Application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

Prior art data storage systems do not efficiently service all types ofdata access requests, data checks, and data status checks. For example,the response time of such communications between devices may beprohibitive in some data storage systems and based on some conditions.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of another embodiment of a dispersedstorage network (DSN) in accordance with the present invention;

FIG. 10 is a flowchart illustrating an example of retrieving an encodeddata slice in accordance with the present invention;

FIG. 11A is a schematic block diagram of an example of separatelyprovisioned memories within a computing device for different purposes inaccordance with the present invention;

FIG. 11B is a schematic block diagram of another example of separatelyprovisioned memories within a computing device for different purposes inaccordance with the present invention; and

FIG. 12 is a diagram illustrating an embodiment of a method forexecution by one or more computing devices in accordance with thepresent invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/r may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-8. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for pubic access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), interne small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 60 is shown inFIG. 6. As shown, the slice name (SN) 60 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

F 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a schematic block diagram of another embodiment 900 of adispersed storage network (DSN) that includes the distributed storageand task (DST) processing unit 16, the network 24 of FIG. 1, and a setof storage units 1-n such as based on SUs 36 such as with respect toFIG. 3 or FIG. 7. Each storage unit includes a processing module and/orcomputing core 26, a fast memory 910, and a memory 920. The memory 920may be implemented utilizing the various types of memory such as a harddrive and/or hard disk drive (HDD). The fast memory 910 may beimplemented utilizing the memory 920 with access characteristics thatare faster than the memory 920 (e.g., solid-state memory, random accessmemory (RAM), and/or any other fast memory 910 device). Each storageunit may be implemented utilizing a DST execution unit that may beimplemented utilizing the computing device 12, 14, 16, the managing unit18, and/or the integrity processing unit 20 such as with respect to FIG.1, a SU 36 such as with respect to FIG. 3 or FIG. 7, and/or any otherdevice implemented within a DSN to perform operations associated with aDST execution unit. The DSN functions to retrieve the encoded dataslice. In some examples, the fast memory 910 is characterized assubstantially and/or approximately faster-responsive, faster-accessible,faster-operative, etc. memory than the memory 920. As a specificexample, the fast memory 910 when implemented as solid state memory willbe faster-responsive, faster-accessible, faster-operative, etc. memorythan the memory 920 when implemented as a hard disk drive (HDD).

In an example of operation of the retrieving of the encoded data slice,the processing module 84 of the storage unit 1 accesses the fast memory910 to determine whether a slice 1-1 is stored in the memory 920 whenreceiving a read request for slice 1-1, where data has been dispersedstorage error encoded to produce a plurality of N sets of encoded dataslices 1-n for storage in the memories of the storage units, where theDST processing unit 16 sends, via the network 24, a set of read slicerequests 1-n that includes the read request for slice 1-1. Thedetermining includes at least one of accessing a slice name and statuslist in the fast memory 910, interpreting the list, and indicatingwhether the slice is stored in the memory 920 based on theinterpretation of the list. For example, the processing module 84indicates that the slice 1-1 is available for retrieval when theretrieved list from the fast memory 910 indicates that the slice 1-1 isstored in the memory 920. When the requested slice is stored in thememory 920, the processing module 84 of the storage unit 1 sends, viathe network 24, the requested slice 1-1 to the DST processing unit 16 asa read response of a set of read responses for slices 1-n.

The processing module 84 of the storage unit 2 accesses the fast memory910 of the storage unit 2 to determine whether a slice 2-1 is stored inthe memory 920 of the storage unit 2 when receiving a read request forslice 2-1. The determining includes at least one of accessing a slicename and status list in from fast memory 910 of the storage unit 2,interpreting the list, and indicating whether the slice is stored in thememory 920 of the storage unit 2 based on the interpretation of thelist. For example, the processing module 84 of the storage unit 2indicates that the slice 2-1 is not available for retrieval when theretrieved list from the fast memory of the storage unit 2 indicates thatthe slice 2-1 is not stored in the memory 920. When the requested sliceis not stored in the memory 920, the processing module $0 for thestorage unit 2 sends, via the network 24, a read response for slice 2-1to the DST processing unit 16, where the response indicates that therequested slice 2-1 is not available.

FIG. 10 is a flowchart illustrating an example of retrieving an encodeddata slice. The method 1000 includes a step 1010 where a processingmodule (e.g., of a storage unit) receives a read request for an encodeddata slice, where the read request includes one or more of a slice namea revision level, a memory identifier, a fast memory identifier, amemory address, and a fast memory address. The method 1000 continues atthe step 1020 where the processing module accesses a fast memory todetermine whether the encoded data slice is available. For example, theprocessing module accesses a slice name and status list within the fastmemory, interprets the slice name and status list, and indicates thatthe requested encoded data slice is available when the interpretationindicates that the encoded data slice is stored in a memory (e.g.,another memory). The method 1000 branches to the step 1042 where theprocessing module generates a read response indicating that the encodeddata slices not available when the encoded data slices not available.The method 1000 continues to the next step 1044 where the processingmodule accesses a memory to retrieve the encoded data slice when theencoded data slice is available.

When the encoded data slice is available, the method 1000 continues atthe step 1030 where the processing module accesses a memory to retrieveencoded data slice. For example, the processing module identifies amemory device, identifies an address of the identified memory device,and accesses the identified memory device at the identified at addressto retrieve encoded data slice. The method 1000 continues at the step1040 where the processing module sends the retrieved encoded data sliceto a requesting entity.

When the encoded data slice is not available, the method 1000 continuesat the step 1042 where the processing module generates a read responseindicating that the encoded data slice is not available. The generatingincludes producing the response to include one or more of the slicename, a revision level, and an indicator that the slices not available.The method 1000 continues at the step 1044 where the processing modulesends the read response to the requesting entity.

FIG. 11A is a schematic block diagram of an example 1101 of separatelyprovisioned memories within a computing device for different purposes inaccordance with the present invention. A computing device 12 or 16include fast memory/random access memory (RAM) 1110 (e.g., such as solidstate memory) and memory 1120 (e.g., a hard disk drive (HDD)). Ingeneral, the fast memory/RAM 1110 is any type of memory that is veryquickly responsive and can be accessed very quickly as opposed to moreconventional memory such as a HDD that is relatively more slowlyresponsive to accesses thereto.

In an example of operation and implementation, a computing deviceincludes an interface configured to interface and communicate with adispersed storage network (DSN), a memory that stores operationalinstructions, and a processing module operably coupled to the interfaceand memory such that the processing module, when operable within thecomputing device based on the operational instructions, is configured toperform various operations.

For example, computing device 12 or 16 receives from another computingdevice a data access request for an encoded data slice (EDS) associatedwith a data object. Note that the data access request includes a dataaccess request slice name for the EDS associated with the data object.Then, the computing device 12 or 16 compares the data access requestslice name with a plurality of slice names stored within the RAM,wherein the plurality of slice names are respectively associated with aplurality of encoded data slices (EDSs) stored within the HDD.

When the data access request slice name compares unfavorably with theplurality of slice names, the computing device 12 or 16 transmits anempty data access response that includes no EDS to the other computingdevice. When the data access request slice name compares favorably withat least one of the plurality of slice names, the computing device 12 or16 then transmits retrieves, from the HDD, an EDS of the plurality ofEDSs having a corresponding slice name that compares favorably with thedata access request slice name and transmits a data access response thatincludes the EDS of the plurality of EDSs having the corresponding slicename to the other computing device.

In some examples, note that the data object is segmented into aplurality of data segments, and a data segment of the plurality of datasegments is dispersed error encoded in accordance with dispersed errorencoding parameters to produce a set of encoded data slices (EDSs). Notethat each EDS of the set of EDS having a respective slice name, and theset of EDSs are distributedly stored among a plurality of storage units(SUs) within the DSN. A decode threshold number of EDSs are needed torecover the data segment, a read threshold number of EDSs provides forreconstruction of the data segment, and a write threshold number of EDSsprovides for a successful transfer of the set of EDSs from a first atleast one location in the DSN to a second at least one location in theDSN.

Note that the computing device may be located at a first premises thatis remotely located from at least one SU of the primary SUs or pluralityof secondary SUs the within the DSN. Also, note that the computingdevice may be of any of a variety of types of devices as describedherein and/or their equivalents including a SU of any group and/or setof SUs within the DSN, a wireless smart phone, a laptop, a tablet, apersonal computers (PC), a work station, and/or a video game device.Note also that the DSN may be implemented to include or be based on anyof a number of different types of communication systems including awireless communication system, a wire lined communication systems, anon-public intranet system, a public internet system, a local areanetwork (LAN), and/or a wide area network (WAN).

FIG. 11B is a schematic block diagram of another example 1102 ofseparately provisioned memories within a computing device for differentpurposes in accordance with the present invention. The computing device12 or 16 stores slice names (e.g., SN1_1 through SN 1_Y) in the fastmemory/RAM 1110 (e.g., such as solid state memory) and stores encodeddata slices (EDSs) (e.g., EDS 1_1 through EDS 1_Y) in the memory 1120(e.g., a hard disk drive (HDD)). In general, any other desiredidentifiers may also be stored in the fast memory/RAM 1110.

A computing device 12 or 16 include fast memory/random access memory(RAM) 1110 (e.g., such as solid state memory) and memory 1120 (e.g., ahard disk drive (HDD)). In general, the fast memory/RAM 1110 is any typeof memory that is very quickly responsive and can be accessed veryquickly as opposed to more conventional memory such as a HDD that isrelatively more slowly responsive to accesses thereto.

In an example of operation and implementation, the computing device 12or 16 compares a revision level for the EDS associated with the dataobject that is included within the data access request to a plurality ofrevision levels stored within the RAM. Note that the plurality ofrevision levels are associated respectively with the plurality of slicenames stored within the RAM. When the data access request slice namecompares unfavorably with the plurality of slice names and when therevision level for the EDS associated with the data object comparesunfavorably with the plurality of revision levels, the computing device12 or 16 transmits the empty data access response to the other computingdevice.

When the data access request slice name compares favorably with theplurality of slice names and when the revision level for the EDSassociated with the data object compares unfavorably with the pluralityof revision levels, the computing device 12 or 16 transmits the emptydata access response to the other computing device. When the data accessrequest slice name compares favorably with at least one of the pluralityof slice names and when the revision level for the EDS associated withthe data object compares favorably with at least one of the plurality ofrevision levels, then the computing device 12 or 16 retrieves, from theHDD, the EDS of the plurality of EDSs having the corresponding slicename that compares favorably with the data access request slice name anda corresponding revision level that compares favorably with the revisionlevel for the EDS associated with the data object. The computing device12 or 16 then transmits the data access response that includes the EDSof the plurality of EDSs having the corresponding slice name and thecorresponding revision level that compares favorably with the revisionlevel for the EDS associated with the data object to the other computingdevice.

In some examples, the data access request for the EDS associated withthe data object is based on any one or more of a check request involvingthe EDS associated with the data object, a read request involving theEDS associated with the data object, a write request involving the EDSassociated with the data object, a rebuild request involving the EDSassociated with the data object, a rebuild scanning request involvingthe EDS associated with the data object, a reallocation requestinvolving the EDS associated with the data object, a rebalancing requestinvolving the EDS associated with the data object, a synchronizationrequest between mirrored vault operations involving the EDS associatedwith the data object, and/or a trimmed write request involving the EDSassociated with the data object based on fewer than all of a set ofencoded data slices (EDSs) generated when the data object is segmentedinto a plurality of data segments and a data segment of the plurality ofdata segments is dispersed error encoded in accordance with dispersederror encoding parameters to produce the set of EDSs.

Note that different sets of trimmed copies of EDSs may be based on andinclude different EDSs therein. For example, a trimmed copy may beinitially generated and included/stored in another set of SUs.Subsequently, such trimmed copy can be fully built out to include all ofthe EDSs of a set of EDSs in a set of SUs in which a trimmed copy ofEDSs is initially stored. In some examples, such completion of a trimmedset of EDSs to generate a full copy set of EDSs may be made later whenDSN conditions may be more amendable to do so (e.g., less traffic,period of lower activity, freed up processing resources, etc.). Inaddition, note that as certain versions of EDSs get updated (e.g., whenthe information dispersal algorithm (IDA), or original version of EDSs,or baseline set of EDSs, etc. gets updated), then other versions (e.g.,copies of those EDSs, trimmed copies of those EDSs, etc.) can be updatedappropriately in accordance with the various operations and conditionsas described herein. This disclosure presents a novel means by whichvarious sets of EDSs including copies and/or trimmed copies of EDSs of abaseline set of EDSs can be synchronized in terms of version level amongother characteristics. When one or more SUs store EDSs that are not of acurrent version, then that SU can be directed to perform by another SUand/or computing device or can perform independently a rebuild of thoseEDSs at the proper revision level and/or request such proper revisionlevel EDSs from another one or more SUs that store the proper revisionlevel of EDSs.

In some examples, when the data access request slice name comparesunfavorably with the plurality of slice names, the computing device 12or 16 generates the empty data access response that includes no EDSwithout accessing the HDD. In some examples, note that the computingdevice is located at a first premises that is remotely located from atleast one storage unit (SU) of a plurality of storage units (SUs) withinthe DSN that distributedly store a set of EDSs that includes the EDSassociated with the data object. Note that the computing device 12 or 16may be any type of devices including a storage unit (SU) within the DSN,a wireless smart phone, a laptop, a tablet, a personal computers (PC), awork station, and/or a video game device. Note also that the DSN may beimplemented to include or be based on any of a number of different typesof communication systems including a wireless communication system, awire lined communication systems, a non-public intranet system, a publicInternet system, a local area network (LAN), and/or a wide area network(WAN).

FIG. 12 is a diagram illustrating an embodiment of a method 1200 forexecution by one or more computing devices in accordance with thepresent invention.

The method 1200 begins in step 1210 by receiving (e.g., via an interfaceconfigured to interface and communicate with a dispersed storage network(DSN)) from another computing device a data access request for anencoded data slice (EDS) associated with a data object. Note that thedata access request includes a data access request slice name for theEDS associated with the data object.

The method 1200 continues in step 1220 by comparing the data accessrequest slice name with a plurality of slice names stored within randomaccess memory (RAM) of the computing device. Note that the plurality ofslice names are respectively associated with a plurality of encoded dataslices (EDSs) stored within the HDD.

The method 1200 then operates in step 1230 by determining whether thedata access request slice name compares favorably or unfavorably withthe plurality of slice names.

When the data access request slice name compares unfavorably with theplurality of slice names, the method 1200 then continues in step 1240 bytransmitting via the interface an empty data access response thatincludes no EDS to the other computing device. Alternatively, when thedata access request slice name compares favorably with at least one ofthe plurality of slice names, the method 1200 then continues in step1250 by retrieving, from an hard disk drive (HDD) of the computingdevice, an EDS of the plurality of EDSs having a corresponding slicename that compares favorably with the data access request slice name.Then, the method 1200 then continues in step 1260 by transmitting viathe interface a data access response that includes the EDS of theplurality of EDSs having the corresponding slice name to the othercomputing device.

When a dispersed storage (DS) unit has fast-access memory devicesavailable, but with insufficient capacity to store all slices, it mayuse those fast-access memory devices to store slice names and revisions.This enables rapid responses to be generated for listing requests, checkrequests, and read requests for slices which do not exist. The DS unit,upon receiving a read request, will first check the fast-access memorydevice to determine the list of revisions which it stores for therequested slice name. If it determines that no such revisions are heldon this DS unit, it can immediately return an empty read responsewithout having to incur any IO to the memory devices for which theinput/output (I/O) operations and processing may be expensive (e.g., interms of speed, latency, etc.). The capability to efficiently handlereads for non-existent slices is important to a number of features,including Trimmed Writes, Target Widths, information dispersal algorithm(IDA)+Copy, and other situations. Fast check responses (e.g., veryquickly provided response(s) from a device based on that device making adetermination of status of EDS(s) stored therein by accessinginformation stored in fast memory indicating whether the requestedEDS(s) and/or appropriate revision level(s) are stored therein) areuseful for guaranteeing consistency and for meeting Read Thresholdcheaply, while fast list request responses aid in rebuild scanning,reallocation, rebalancing, and synching between mirrored vaultoperations.

In general, there can be many operations performed within a DSN withoutneeding to read an actual EDS. As such, the slice name(s) may beimplemented in fast access memory (e.g., solid state, RAM, etc. memoryvs. hard disk drive (HDD) memory). As such, the computing device canrespond much more quickly by using slice names and appropriate revisionlevel before accessing the actual storage medium (e.g., HDD) and gettingthe actual data (e.g., EDS(s)).

For example, each computing device and/or SU can be implemented to havea substantial amount of fast memory (e.g., RAM, solid state memory,etc.). There is a dividing line between RAM and HDDs within thecomputing device and/or SU. For example, the computing device and/or SUincludes RAM that is used for processing, but then the computing deviceand/or SU also uses solid state for storage of slice names as well. Thecomputing device and/or SU includes a mapping of where, for each of theslices, are physically stored the slice names and where the actualslices are stored in the device (e.g., in the HDD). As such, thecomputing device and/or SU includes 2 types of memory within the device(e.g., fast memory such as RAM, solid state memory, etc. and memory suchas HDD). The computing device and/or SU puts the slice names (andrevision numbers) in the fast memory and the actual data in the HDD. Thecomputing device and/or SU can respond immediately to any data accessrequests if does not have the data without having to check or access theHDD by checking the slice names in the fast memory such as RAM, solidstate memory, etc. In addition, note that the computing device and/or SUmay also bifurcate the processing such that the computing device and/orSU could have implemented dedicated processing for messaging requests,etc. and then additional processing (and hardware) to access the actualdata (input/output requests).

It is noted that terminologies as may be used herein such as hit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A computing device comprising: an interfaceconfigured to interface and communicate with a distributed storagenetwork (DSN); memory that stores operational instructions; and aprocessing module operably coupled to the interface and to the memory,wherein the processing module, when operable within the computing devicebased on the operational instructions, is configured to: transmit, to astorage unit (SU), a data access request for an encoded data slice (EDS)associated with a data object, wherein the data access request includesa data access request identifier for the EDS associated with the dataobject, wherein the SU includes another memory that includes randomaccess memory (RAM) and a hard disk drive (HDD); and receive, from theSU, an empty data access response that includes no EDS based on anunfavorable comparison, as performed by the SU, of the data accessrequest identifier with a plurality of identifiers stored within theRAM, wherein the plurality of identifiers are respectively associatedwith a plurality of encoded data slices (EDSs) stored within the HDD ofthe SU.
 2. The computing device of claim 1, wherein the processingmodule, when operable within the computing device based on theoperational instructions, is further configured to: based on a favorablecomparison, as performed by the SU, of the data access requestidentifier with at least one of the plurality of identifiers, receive,from the SU, a data access response that includes an EDS of theplurality of EDSs having a corresponding identifier that is retrievedfrom the HDD of the SU.
 3. The computing device of claim 1, wherein thedata object is segmented into a plurality of data segments, wherein adata segment of the plurality of data segments is dispersed errorencoded in accordance with dispersed error encoding parameters toproduce a set of encoded data slices (EDSs), wherein each EDS of the setof EDS having a respective identifier, wherein the set of EDSs aredistributedly stored among a plurality of storage units (SUs) includingthe SU within the DSN, wherein a decode threshold number of EDSs areneeded to recover the data segment, wherein a read threshold number ofEDSs provides for reconstruction of the data segment, wherein a writethreshold number of EDSs provides for a successful transfer of the setof EDSs from a first at least one location in the DSN to a second atleast one location in the DSN.
 4. The computing device of claim 1,wherein the processing module, when operable within the computing devicebased on the operational instructions, is further configured to: basedon comparison, as performed by the SU, of a revision level for the EDSassociated with the data object that is included within the data accessrequest to a plurality of revision levels stored within the RAM, whereinthe plurality of revision levels are associated respectively with theplurality of identifiers stored within the RAM, receive, from the SU,the empty data access response that includes no EDS without the SUaccessing the HDD based on at least one of: unfavorable comparison, asperformed by the SU, of the data access request identifier with theplurality of identifiers and unfavorable comparison, as performed by theSU, of the revision level for the EDS associated with the data objectwith the plurality of revision levels; or favorable comparison, asperformed by the SU, of the data access request identifier with theplurality of identifiers and unfavorable comparison, as performed by theSU, of the revision level for the EDS associated with the data objectwith the plurality of revision levels.
 5. The computing device of claim1, wherein the data access request for the EDS associated with the dataobject is based on at least one of: a check request involving the EDSassociated with the data object; a read request involving the EDSassociated with the data object; a write request involving the EDSassociated with the data object; a rebuild request involving the EDSassociated with the data object; a rebuild scanning request involvingthe EDS associated with the data object; a reallocation requestinvolving the EDS associated with the data object; a rebalancing requestinvolving the EDS associated with the data object; a synchronizationrequest between mirrored vault operations involving the EDS associatedwith the data object; or a trimmed write request involving the EDSassociated with the data object based on fewer than all of a set ofencoded data slices (EDSs) generated when the data object is segmentedinto a plurality of data segments and a data segment of the plurality ofdata segments is dispersed error encoded in accordance with dispersederror encoding parameters to produce the set of EDSs.
 6. The computingdevice of claim 1, wherein the computing device is located at a firstpremises that is remotely located from at least one storage unit (SU) ofa plurality of storage units (SUs) that includes the SU within the DSNthat distributedly store a set of EDSs that includes the EDS associatedwith the data object.
 7. The computing device of claim 1 furthercomprising: another SU within the DSN, a wireless smart phone, a laptop,a tablet, a personal computers (PC), a work station, or a video gamedevice.
 8. The computing device of claim 1, wherein the DSN includes atleast one of a wireless communication system, a wire lined communicationsystems, a non-public intranet system, a public internet system, a localarea network (LAN), or a wide area network (WAN).
 9. A computing devicecomprising: an interface configured to interface and communicate with adistributed storage network (DSN); memory that stores operationalinstructions; and a processing module operably coupled to the interfaceand to the memory, wherein the processing module, when operable withinthe computing device based on the operational instructions, isconfigured to: transmit, to a storage unit (SU), a data access requestfor an encoded data slice (EDS) associated with a data object, whereinthe data access request includes a data access request identifier forthe EDS associated with the data object, wherein the SU includes anothermemory that includes random access memory (RAM) and a hard disk drive(HDD), wherein the data access request for the EDS associated with thedata object is based on at least one of: a check request involving theEDS associated with the data object; a read request involving the EDSassociated with the data object; a write request involving the EDSassociated with the data object; a rebuild request involving the EDSassociated with the data object; a rebuild scanning request involvingthe EDS associated with the data object; a reallocation requestinvolving the EDS associated with the data object; a rebalancing requestinvolving the EDS associated with the data object; a synchronizationrequest between mirrored vault operations involving the EDS associatedwith the data object; or a trimmed write request involving the EDSassociated with the data object based on fewer than all of a set ofencoded data slices (EDSs) generated when the data object is segmentedinto a plurality of data segments and a data segment of the plurality ofdata segments is dispersed error encoded in accordance with dispersederror encoding parameters to produce the set of EDSs; receive, from theSU, an empty data access response that includes no EDS based on anunfavorable comparison, as performed by the SU, of the data accessrequest identifier with a plurality of identifiers stored within theRAM, wherein the plurality of identifiers are respectively associatedwith a plurality of encoded data slices (EDSs) stored within the HDD ofthe SU; and receive, from the SU, a data access response that includesan EDS of the plurality of EDSs having a corresponding identifier thatis retrieved from the HDD of the SU based on a favorable comparison, asperformed by the SU, of the data access request identifier with at leastone of the plurality of identifiers.
 10. The computing device of claim9, wherein the data object is segmented into a plurality of datasegments, wherein a data segment of the plurality of data segments isdispersed error encoded in accordance with dispersed error encodingparameters to produce a set of encoded data slices (EDSs), wherein eachEDS of the set of EDS having a respective identifier, wherein the set ofEDSs are distributedly stored among a plurality of storage units (SUs)including the SU within the DSN, wherein a decode threshold number ofEDSs are needed to recover the data segment, wherein a read thresholdnumber of EDSs provides for reconstruction of the data segment, whereina write threshold number of EDSs provides for a successful transfer ofthe set of EDSs from a first at least one location in the DSN to asecond at least one location in the DSN.
 11. The computing device ofclaim 9, wherein the processing module, when operable within thecomputing device based on the operational instructions, is furtherconfigured to: based on comparison, as performed by the SU, of arevision level for the EDS associated with the data object that isincluded within the data access request to a plurality of revisionlevels stored within the RAM, wherein the plurality of revision levelsare associated respectively with the plurality of slice identifiersstored within the RAM, receive, from the SU, the empty data accessresponse that includes no EDS without the SU accessing the HDD based onat least one of: unfavorable comparison, as performed by the SU, of thedata access request identifier with the plurality of identifiers andunfavorable comparison, as performed by the SU, of the revision levelfor the EDS associated with the data object with the plurality ofrevision levels; or favorable comparison, as performed by the SU, of thedata access request identifier with the plurality of identifiers andunfavorable comparison, as performed by the SU, of the revision levelfor the EDS associated with the data object with the plurality ofrevision levels.
 12. The computing device of claim 9 further comprising:another SU within the DSN, a wireless smart phone, a laptop, a tablet, apersonal computers (PC), a work station, or a video game device.
 13. Thecomputing device of claim 9, wherein the DSN includes at least one of awireless communication system, a wire lined communication systems, anon-public intranet system, a public internet system, a local areanetwork (LAN), or a wide area network (WAN).
 14. A method for executionby a computing device, the method comprising: transmitting, via aninterface configured to interface and communicate with a distributedstorage network (DSN) and to a storage unit (SU), a data access requestfor an encoded data slice (EDS) associated with a data object, whereinthe data access request includes a data access request clicc identifierfor the EDS associated with the data object, wherein the SU includesanother memory that includes random access memory (RAM) and a hard diskdrive (HDD); and receiving, via the interface and from the SU, an emptydata access response that includes no EDS based on an unfavorablecomparison, as performed by the SU, of the data access requestidentifier with a plurality of identifiers stored within the RAM,wherein the plurality of identifiers are respectively associated with aplurality of encoded data slices (EDSs) stored within the HDD of the SU.15. The method of claim 14 further comprising: based on a favorablecomparison, as performed by the SU, of the data access requestidentifier with at least one of the plurality of identifiers, receiving,via the interface and from the SU, a data access response that includesan EDS of the plurality of EDSs having a corresponding identifier thatis retrieved from the HDD of the SU.
 16. The method of claim 14, whereinthe data object is segmented into a plurality of data segments, whereina data segment of the plurality of data segments is dispersed errorencoded in accordance with dispersed error encoding parameters toproduce a set of encoded data slices (EDSs), wherein each EDS of the setof EDS having a respective identifier, wherein the set of EDSs aredistributedly stored among a plurality of storage units (SUs) includingthe SU within the DSN, wherein a decode threshold number of EDSs areneeded to recover the data segment, wherein a read threshold number ofEDSs provides for reconstruction of the data segment, wherein a writethreshold number of EDSs provides for a successful transfer of the setof EDSs from a first at least one location in the DSN to a second atleast one location in the DSN.
 17. The method of claim 14 furthercomprising: based on comparison, as performed by the SU, of a revisionlevel for the EDS associated with the data object that is includedwithin the data access request to a plurality of revision levels storedwithin the RAM, wherein the plurality of revision levels are associatedrespectively with the plurality of identifiers stored within the RAM,receiving, via the interface and from the SU, the empty data accessresponse that includes no EDS without the SU accessing the HDD based onat least one of: unfavorable comparison, as performed by the SU, of thedata access request identifier with the plurality of identifiers andunfavorable comparison, as performed by the SU, of the revision levelfor the EDS associated with the data object with the plurality ofrevision levels; or favorable comparison, as performed by the SU, of thedata access request identifier with the plurality of identifiers andunfavorable comparison, as performed by the SU, of the revision levelfor the EDS associated with the data object with the plurality ofrevision levels.
 18. The method of claim 14, wherein the data accessrequest for the EDS associated with the data object is based on at leastone of: a check request involving the EDS associated with the dataobject; a read request involving the EDS associated with the dataobject; a write request involving the EDS associated with the dataobject; a rebuild request involving the EDS associated with the dataobject; a rebuild scanning request involving the EDS associated with thedata object; a reallocation request involving the EDS associated withthe data object; a rebalancing request involving the EDS associated withthe data object; a synchronization request between mirrored vaultoperations involving the EDS associated with the data object; or atrimmed write request involving the EDS associated with the data objectbased on fewer than all of a set of encoded data slices (EDSs) generatedwhen the data object is segmented into a plurality of data segments anda data segment of the plurality of data segments is dispersed errorencoded in accordance with dispersed error encoding parameters toproduce the set of EDSs.
 19. The method of claim 14, wherein thecomputing device includes another SU within the DSN, a wireless smartphone, a laptop, a tablet, a personal computers (PC), a work station, ora video game device.
 20. The method of claim 14, wherein the DSNincludes at least one of a wireless communication system, a wire linedcommunication systems, a non-public intranet system, a public internetsystem, a local area network (LAN), or a wide area network (WAN).